Understand difference between Machine Learning and AI
In short, AI is any technology that showcases anything that resembles human intelligence. Think of any of your favorite sci-fi films.
However, ML or Machine Learning is a subset of AI that uses mathematical models from data to make decisions.
Brief History of AI
During WWII, genius, computer scientist Alan Turing worked to crack the impossible German forces Enigma Code, a form of communication used to send messages securely and plan attacks. To decipher the code, Turing created the Bombe machine. This machine was “intelligent” and able to learn an eventually crack the code.
Turing’s machine has laid the foundations of what ML and AI are today. Over the decades to follow, researchers were eager to push the boundaries of computer intelligence for the military and for scientific research.
From the creation of the AI programming language, LISP, in the 60s to the eventual creation of IBM’s Deep Blue in the 90s, all of these events have laid the framework for the AI you know today.
Machine Learning
So, what exactly is machine learning? For starters, ML is not as far away as you think.
Tools you use everyday incorporate ML to create better experiences for you. Google even uses your data to optimize advertising. Even your beloved Netflix uses ML to make recommendations of what you should watch. ML learns from large amounts of data to make predictions. “Machine learning algorithms are widely employed and are encountered daily."
"Examples are automatic recommendations when buying a product or voice recognition software that adapts to your voice,” says researchers from the University of Maastricht.
How Does Machine Learning Work?
Machine Learning “learns” using, from a term that you have probably heard thrown around a lot, "neural networks". Neural Networks is where Machine Learning “learns and trains” from a large set of data to determine the probable outcome of a situation.
Without getting overly complicated, neural networks are where a computer would learn for thousands of hours to identify a person or animal in an image or even learn how to translate a language. Nevertheless, much of this process requires a human touch i.e, a programmer to do most of the heavy lifting. ML is basically using large sets of data, hours of training to make predictions on probable outcomes.
Artificial Intelligence
When Machine Learning “comes to life” and moves beyond simple programming and can reflect and interact with people, even on the most basic level, this is where AI comes into play.
You probably get confused by the terms Machine Learning and Artificial Intelligence because they are used interchangeably.
AI is the step beyond ML, yet AI needs ML to reflect and optimize decisions. AI uses what it has gained from ML to simulated intelligence, the same way a human is constantly observing their surrounding environment and making intelligent decisions. AI leads to intelligence or wisdom and the end goal is to simulate natural intelligence to solve complex problems across the world.
The coming AI revolution could tackle some of the world’s most difficult challenges.
Reference: https://interestingengineering.com
